Modeling coordination of electrical grids considering multi-objective functions operation and multiple-time scales

This study introduces a novel long-term stochastic operation simulation approach for power grids, utilizing multi-scenario and multi-time scale coordination. Initially, a set of typical source load scenarios is created using Latin hypercube sampling and simultaneous backward reduction techniques. Deterministic scenarios are then generated to capture the stochastic fluctuation characteristics of renewable energy and load based on the probability distribution of uncertainty variables. Subsequently, the power balance issue for 8760 h annually is transformed into weekly and daily electricity balance problems within a multi-time scale coordinated framework for power grids. This enables effective coordination of system operation plans across different time periods, enhancing the efficiency of stochastic operation simulation solutions. The proposed method is validated using a sample power grid example. Compared to direct 8760-h operation simulation, the solution time is significantly reduced by 73.54% with accelerated calculation. The system operation index closely matches actual operations, with relative errors of key metrics controlled within 0.01%, ensuring high calculation accuracy.